A computing policy is a sequence of rules, where each rule consists of a predicate and an action, and where each action is either “accept” or “reject”. A policy P is said to accept (or reject, respectively) a request iff the action of the first rule in P , that is matched by the request is “accept” (or “reject”, respectively). A pair of policies (P , Q) is called an accept-implication pair iff ...

Let S be a set of n points and let w be a function that assigns non-negative weights to points in S. The additive weighted distance dw(p, q) between two points p, q ∈ S is defined as w(p) + d(p, q) + w(q) if p 6= q and it is zero if p = q. Here, d(p, q) denotes the (geodesic) Euclidean distance between p and q. A graph G(S,E) is called a t-spanner for the additive weighted set S of points if fo...

We present an algorithm that achieves general syndrome decoding of a (n; k; r) linear rank distance code over GF(q m) in O((nr + m) 3 q (m?r)(r?1)) elementary operations. As a consequence, the cryptographic Al schemes Che94, Che96] which rely on this problem are not secure with the proposed parameters. We also derive from our algorithm a bound on the minimal rank distance of a linear code which...

Automated chromosome classification is an essential task in cytogenetics. The genetic disorders and abnormalities that occur to the future generation can be predicted through analysing the various characteristics of the chromosomes. The chromosome classification is mainly based on geometric and morphological features. An effective algorithm for chromosome geometric feature extraction is present...

In this paper, we revisit the problem of computing the kernel of a separable isogeny of degree ` between two elliptic curves defined over a finite field Fq of characteristic p. We describe an algorithm the asymptotic time complexity of which is equal to e O(`(1 + `/p) log q) bit operations. This algorithm is particularly useful when ` > p and as a consequence, we obtain an improvement of the co...

In this paper, a method integrating Q-learning algorithm and simulation technique is proposed to optimize the operation scheduling in container terminals. Firstly Q-learning algorithms for yard cranes and yard trailers are designed to obtain the optimal scheduling strategy of yard cranes and yard trailers. Then Q-learning is combined with simulation to develop an integrating scheduling model in...

We present an efficient algorithm for evaluating an XPath query Q (involving only child and descendant axes) on a streaming XML document D. Previously known in-memory algorithms for XPath evaluation use O(|D|) space and O(|Q||D|) time. Several previous algorithms for the streaming version use Θ(d +c) space and Θ(d|D|) time in the worst case; d is the depth of D, n is the number of location step...

Let Q(2n+2, q) denote the non-singular parabolic quadric in the projective geometry PG(2n+2, q). We describe the implementation in GAP of an algorithm to determine the minimal number of points of a minimal blocking set of Q(4, q), for q = 5, 7

Let E/Q(t) be an elliptic curve and let t0∈Q a rational number for which the specialization Et0 is curve. Given subgroup M of E(Q(t)) with mild conditions coming from relatively large subset SM⊂Q, we provide algorithm that can show map σt0:E(Q(t))→Et0(Q) injective when restricted to M. The set SM effectively computable in certain cases, carry out this computation some explicit examples where E ...

Q-learning is a popular reinforcement learning algorithm, but it can perform poorly in stochastic environments due to overestimating action values. Overestimation is due to the use of a single estimator that uses the maximum action value as an approximation for the maximum expected action value. To avoid overestimation in Qlearning, the double Q-learning algorithm was recently proposed, which u...